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28 votes

Why is it believed that a single-layer perceptron can't solve XOR? Doesn't this example disprove that?

The perceptron has a step activation. This does not. But at a deeper level, what you are showing is that, if we define the neuron's activation function to be XOR (essentially what the mod 2 addition ...
chessprogrammer's user avatar
3 votes
Accepted

Direct formula for calculating the optimum matrix which minimizes the perceptron error

The idea is correct, the last formula is wrong. In general $X$ will not be square, usually one has much more data than parameters. The data points will also be in general position, so that $X$ has ...
Lutz Lehmann's user avatar
2 votes

Direct formula for calculating the optimum matrix which minimizes the perceptron error

As you understand, $E$ is the definition of loss function. This function defines square of the difference between weights applied to $X_i$, namely output of the perception, and $Y_i$ the desired ...
OmG's user avatar
  • 1,826
1 vote

Is the Adaline just a Perceptron that uses Linear activation function and MSE cost function, and all the rest of steps are the same of Perceptron?

Their major difference in terms of learning is mentioned by your own reference of Adaline: The difference between Adaline and the standard perceptron is in how they learn. Adaline unit weights are ...
cinch's user avatar
  • 2,277

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